Set one attribute of a lgb.Dataset
setinfo(dataset, ...) # S3 method for lgb.Dataset setinfo(dataset, name, info, ...)
| dataset | Object of class |
|---|---|
| ... | other parameters |
| name | the name of the field to get |
| info | the specific field of information to set |
the dataset you passed in
The name field can be one of the following:
label: vector of labels to use as the target variable
weight: to do a weight rescale
init_score: initial score is the base prediction lightgbm will boost from
group: used for learning-to-rank tasks. An integer vector describing how to
group rows together as ordered results from the same set of candidate results to be ranked.
For example, if you have a 100-document dataset with group = c(10, 20, 40, 10, 10, 10),
that means that you have 6 groups, where the first 10 records are in the first group,
records 11-30 are in the second group, etc.
# \donttest{ data(agaricus.train, package = "lightgbm") train <- agaricus.train dtrain <- lgb.Dataset(train$data, label = train$label) lgb.Dataset.construct(dtrain) labels <- lightgbm::getinfo(dtrain, "label") lightgbm::setinfo(dtrain, "label", 1 - labels) labels2 <- lightgbm::getinfo(dtrain, "label") stopifnot(all.equal(labels2, 1 - labels)) # }